Introducing tree neighbouring relationship factors in forest pattern spatial analysis: weighted Delaunay triangulation method

Abstract

It is important to quantify and analyze forest spatial patterns for studying biological characteristics, population interaction and the relationship between the population and environment. In this study, the forest spatial structure unit was generated based on the Delaunay triangulation model (DTM), and the weights were generated using the comprehensive values of the tree diameter at breast height, total height and crown width. The distance between neighbors determined by the DTM was weighted to transform the original coordinates of trees into logical coordinates. Then, a weighted spatial pattern (WSP) was developed. After weighting, the neighboring trees were replaced, the replacement ratio was 38.3%, and there was 57.4% of the central tree. Correlation analysis showed that the uniform angle index of the WSP was significantly correlated with the tree size standard deviation under uniformity (r = 0.932) and randomness (r = 0.711). The DTM method not only considers the spatial distance between trees, but also considers the non-spatial attributes of trees. By changing the spatial topological relation between trees, this method further improves the spatial structure measurement of forest.

Keywords

Delaunay triangulation network model / Weighting / Tree spatial pattern / Tree size standard deviation